{"id":"https://openalex.org/W2793613307","doi":"https://doi.org/10.1109/vcip.2017.8305089","title":"Two-stream deep encoder-decoder architecture for fully automatic video object segmentation","display_name":"Two-stream deep encoder-decoder architecture for fully automatic video object segmentation","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2793613307","doi":"https://doi.org/10.1109/vcip.2017.8305089","mag":"2793613307"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2017.8305089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2017.8305089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061294954","display_name":"Jingwei Xu","orcid":"https://orcid.org/0000-0001-8122-7028"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwei Xu","raw_affiliation_strings":["Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002404808","display_name":"Li Song","orcid":"https://orcid.org/0000-0002-7124-5182"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Song","raw_affiliation_strings":["Cooperative Medianet Innovation Center, Shanghai, China","Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cooperative Medianet Innovation Center, Shanghai, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101577089","display_name":"Rong Xie","orcid":"https://orcid.org/0000-0002-8261-5337"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Xie","raw_affiliation_strings":["Cooperative Medianet Innovation Center, Shanghai, China","Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cooperative Medianet Innovation Center, Shanghai, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.3695,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7115527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8759576082229614},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7783292531967163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7224635481834412},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6941526532173157},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6009151935577393},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5239099264144897},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5005626678466797},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.49283623695373535},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4301171898841858},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37817513942718506},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08692559599876404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8759576082229614},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7783292531967163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7224635481834412},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6941526532173157},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6009151935577393},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5239099264144897},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5005626678466797},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.49283623695373535},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4301171898841858},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37817513942718506},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08692559599876404},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip.2017.8305089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2017.8305089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327718","display_name":"Shanghai Key Laboratory of Digital Media Processing and Transmission","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W65124300","https://openalex.org/W1934184906","https://openalex.org/W2031489346","https://openalex.org/W2037954058","https://openalex.org/W2113708607","https://openalex.org/W2117539524","https://openalex.org/W2138682569","https://openalex.org/W2156303437","https://openalex.org/W2212077366","https://openalex.org/W2294182682","https://openalex.org/W2322739735","https://openalex.org/W2402395722","https://openalex.org/W2412782625","https://openalex.org/W2460260369","https://openalex.org/W2463175074","https://openalex.org/W2470139095","https://openalex.org/W2564998703","https://openalex.org/W2963253279","https://openalex.org/W4239147634","https://openalex.org/W6682864246"],"related_works":["https://openalex.org/W3203142394","https://openalex.org/W4390516098","https://openalex.org/W4302615923","https://openalex.org/W2181948922","https://openalex.org/W2542937328","https://openalex.org/W1974101135","https://openalex.org/W2351061015","https://openalex.org/W2384362569","https://openalex.org/W2221419418","https://openalex.org/W1522196789"],"abstract_inverted_index":{"We":[0],"propose":[1,92],"a":[2,42,93,98],"two-stream":[3],"Deep":[4],"Encoder-Decoder":[5,36],"architecture":[6],"to":[7,75,81,96],"tackle":[8],"the":[9,33,52,56,83],"task":[10],"of":[11,58,85],"fully":[12],"automatic":[13],"video":[14,87],"object":[15,88],"segmentation.":[16],"Both":[17],"two":[18,72,106],"streams,":[19],"i.e.,":[20],"ImSeg-Stream":[21],"(for":[22,28],"static":[23],"image":[24],"segmentation)":[25],"and":[26,48,61,121],"MoSeg-Stream":[27],"optical":[29],"flow":[30],"segmentation),":[31],"hold":[32],"totally":[34],"same":[35],"architecture.":[37],"The":[38],"Encoder":[39],"part":[40,54],"generates":[41],"low-resolution":[43],"mask":[44,60],"with":[45],"accurate":[46],"locations":[47],"smooth":[49],"boundaries,":[50],"while":[51],"Decoder":[53],"refines":[55],"details":[57],"initial":[59],"enlarges":[62],"its":[63],"resolution":[64],"via":[65],"integrating":[66],"lower-level":[67],"features":[68],"progressively.":[69],"At":[70],"last":[71],"streams":[73],"learn":[74],"integrate":[76],"for":[77,102],"better":[78],"results.":[79],"Moreover,":[80],"handle":[82],"problem":[84],"inadequate":[86],"segmentation":[89,119],"datasets,":[90],"we":[91],"seeking":[94],"strategy":[95],"generate":[97],"large-scale":[99],"handcrafted":[100],"dataset":[101],"training.":[103],"Experiments":[104],"on":[105],"standard":[107],"datasets":[108],"demonstrate":[109],"that":[110],"proposed":[111],"method":[112],"outperforms":[113],"most":[114],"state-of-the-art":[115],"methods":[116],"in":[117],"both":[118],"accuracy":[120],"run":[122],"time.":[123]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
